Decrease in gamma-band activity tracks sequence learning.

Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30-100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces.

Common and unique responses to dopamine agonist therapy and deep brain stimulation in Parkinson's disease: an H(2)(15)O PET study.

BACKGROUND: Dopamine agonist therapy and deep brain stimulation (DBS) of the subthalamic nucleus (STN) are antiparkinsonian treatments that act on a different part of the basal ganglia-thalamocortical motor circuitry, yet produce similar symptomatic improvements. OBJECTIVE/HYPOTHESIS: The purpose of this study was to identify common and unique brain network features of these standard treatments. METHODS: We analyzed images produced by H(2)(15)O positron emission tomography (PET) of patients with Parkinson's disease (PD) at rest. Nine patients were scanned before and after injection of apomorphine, and 11 patients were scanned while bilateral stimulators were off and while they were on. RESULTS: Both treatments produced common deactivations of the neocortical sensorimotor areas, including the supplementary motor area, precentral gyrus, and postcentral gyrus, and in subcortical structures, including the putamen and cerebellum. We observed concomitant activations of the superior parietal lobule and the midbrain in the region of the substantia nigra/STN. We also detected unique, treatment-specific changes with possible motor-related consequences in the basal ganglia, thalamus, neocortical sensorimotor cortex, and posterolateral cerebellum. Unique changes in nonmotor regions may reflect treatment-specific effects on verbal fluency and limbic functions. CONCLUSIONS: Many of the common effects of these treatments are consistent with the standard pathophysiologic model of PD. However, the common effects in the cerebellum are not readily explained by the model. Consistent deactivation of the cerebellum is interesting in light of recent reports of synaptic pathways directly connecting the cerebellum and basal ganglia, and may warrant further consideration for incorporation into the model.

Chaos game representation of human pallidal spike trains.

Many studies have demonstrated the presence of scale invariance and long-range correlation in animal and human neuronal spike trains. The methodologies to extract the fractal or scale-invariant properties, however, do not address the issue as to the existence within the train of fine temporal structures embedded in the global fractal organisation. The present study addresses this question in human spike trains by the chaos game representation (CGR) approach, a graphical analysis with which specific temporal sequences reveal themselves as geometric structures in the graphical representation. The neuronal spike train data were obtained from patients whilst undergoing pallidotomy. Using this approach, we observed highly structured regions in the representation, indicating the presence of specific preferred sequences of interspike intervals within the train. Furthermore, we observed that for a given spike train, the higher the magnitude of its scaling exponent, the more pronounced the geometric patterns in the representation and, hence, higher probability of occurrence of specific subsequences. Given its ability to detect and specify in detail the preferred sequences of interspike intervals, we believe that CGR is a useful adjunct to the existing set of methodologies for spike train analysis.